49results about How to "Realize closed-loop management" patented technology

The invention relates to the technical field of electrical safety, in particular to an electrical operator behavior analysis and safety risk prevention and control system which comprises a behavior data acquisition module, a data preprocessing module, a behavior analysis module, a historical risk database, a safety risk assessment module and a real-time early warning module. Wherein the behavior data acquisition module is used for acquiring behavior data and environment data of operating personnel; the behavior analysis module is used for constructing a behavior recognition model; the security risk assessment module is used for performing multi-dimensional risk assessment; the real-time early warning module is used for sending out early warning signals in various forms; according to the invention, through combination of accurate behavior feature identification, multi-dimensional risk assessment and a dynamic early warning technology, the problems of insufficient real-time monitoring of operation behaviors, incomplete risk assessment and untimely early warning response in the prior art are solved, and the safety and risk prevention and control capability in the electrical operation process are improved.

The invention relates to the technical field of concrete electric pole manufacturing, and discloses an optimized steel fiber anti-crack ultra-high performance concrete centrifugal electric pole manufacturing method and system. The method comprises the following steps: dividing an electric pole manufacturing process into a plurality of manufacturing units according to production batches, and collecting material component data, process setting data and online detection data in each manufacturing unit to form a multi-source production data set; calculating an anti-cracking performance index and a strength performance index based on a multi-source production data set, and dynamically outputting an initial process correction value through a dual-threshold monitoring mechanism and a performance adjustment model; performing adaptive adjustment on the initial process correction value of each manufacturing unit according to the production correlation between the adjacent manufacturing units to generate an adjusted process correction value; and carrying out serialization processing on the adjusted process correction value, and outputting a production optimization instruction which is applied to a manufacturing execution process. According to the method, electric pole manufacturing whole-process data integration and dynamic process optimization are achieved, and the production efficiency and the product quality stability can be improved.

The invention relates to the technical field of facility agriculture intelligent monitoring, and discloses a crop disease and insect pest internet-of-things image recognition method and system, and the method comprises the steps: carrying out the data collection and preprocessing, and building a crop growth file; performing illumination characteristic analysis and adaptive enhancement on the original image; performing quality evaluation on the image subjected to quality optimization, calculating a comprehensive quality score and performing screening; a crop growth stage is identified, and multi-scale features are extracted; constructing an agricultural pest knowledge base and estimating a pest prior probability, projecting the multi-scale feature vector to a discrimination subspace and performing weighted fusion according to the prior probability; carrying out double weighting on the environment adaptive fusion feature vector, and carrying out pest and disease identification through a hierarchical classification strategy; performing multi-source evidence fusion to obtain a final recognition result, and generating prevention and treatment suggestions in combination with an agricultural pest knowledge base; the accuracy and environmental adaptability of pest and disease identification are improved.

The utility model relates to the technical field of monitoring of thermal power plant, especially disclose a kind of real-time monitoring device of thermal power plant index parameter based on MIS system. The device is with main frame as core support, main frame upper end fixed monitoring camera device and meteorological sensor group, for collecting field video and environmental parameter;Middle region is fixed display and control box through collar and arc connecting piece, realize data real-time display and remote transmission;Lower end is equipped with grounding component, convex plate and connecting seat, connecting seat can make main frame around its deflection, cooperate with orientation adjusting of positioning rod, and convex plate and connecting plate convex groove adapt to promote stability.The device solves the problem that the existing monitoring device is inconvenient to adjust the orientation, needs to be disassembled as a whole for maintenance, and has poor grounding anti-interference, has the characteristics of flexible adjustment, efficient maintenance and reliable grounding, can adapt to the high temperature, high dust and strong electromagnetic interference environment of thermal power plant, realize the efficient integration of index parameter and MIS system.

The invention discloses a tax risk identification method and system based on multi-source data comparison, and the method comprises the steps: collecting the multi-source data of a target subject and an associated subject from a tax, invoice and commercial credit investigation system, and constructing a data set; extracting time series data of a preset key risk index in a preset observation time period, calculating a volatility and a deviation degree, and generating a dynamic risk feature vector representing each subject risk condition; constructing a risk conduction network based on the association relationship between the target subject and the association subject; calculating the time sequence correlation of the dynamic risk feature vectors respectively corresponding to the target main body node and the associated main body node in a specific time window; when the correlation coefficient exceeds a preset threshold value, it is judged that risk collaboration exists, the associated subjects corresponding to the associated subject nodes are marked as high-risk clusters, and direct associated tax risks are evaluated. According to the invention, dynamic accurate identification and quantitative prevention and control of tax risks are realized, and accuracy and efficiency are improved.

The invention belongs to the technical field of software management, and provides a project source code version issuing management and control method, system and device based on continuous integration and continuous release and a computer readable storage medium, and the method comprises the following steps: S1, establishing data interaction with a source code management tool Gitlab and a project management system, and creating and submitting a version issuing request, establishing association between the development task / Bug and the source code; step S2: regularly executing publishing operation: merging source codes in all submitted version issuing requests to a test branch, and automatically constructing and publishing the source codes to a test environment; s3, a test plan is made according to the edition issuing content, and testing is carried out; and S4, after the test is completed, operating the version issuing requests one by one. According to the method, closed-loop management of continuous integration and continuous release of development, testing and systems is realized, on one hand, source codes needing to be released and source codes not needing to be released are prevented from being automatically integrated together for construction, and on the other hand, the collaboration of developers and testers is improved.

The invention relates to the technical field of image recognition, and discloses a mushroom growth state-based yield prediction method and device, and the method comprises the steps: collecting the time sequence data of mushrooms, determining the two-dimensional feature data and three-dimensional feature data of mushroom sporocarp according to the time sequence data, and carrying out the calculation of the two-dimensional feature data and the three-dimensional feature data; and inputting the two-dimensional feature data and the three-dimensional feature data into a prediction network to calculate a real-time growth rate, when the real-time growth rate is within a normal growth rate range and the mushrooms are in a target growth stage, obtaining a yield prediction result of the mushrooms through a multivariable regression model, and when the real-time growth rate is not within the normal growth rate range, obtaining a yield prediction result of the mushrooms through the multivariable regression model. And determining that the mushrooms are in an abnormal growth state and generating abnormal growth alarm information. Therefore, by implementing the method, the feature recognition precision can be improved through refined image analysis, the reliability and accuracy of growth state judgment and yield prediction are improved, the monitoring accuracy of the mushroom growth state is improved, the yield prediction accuracy and the intelligent degree are further improved, and the labor cost is reduced.

The utility model discloses a medicine container destruction equipment relates to medical waste technical field, wherein, medicine container destruction equipment includes frame, and the frame has first feeding opening, and verification module can at least check the identity of operator and the information of medicine container to be destroyed, the smashing module has the feeding port and the discharge gate, the feeding port is linked with first feeding opening, and the smashing module is used for smashing the medicine container to be destroyed of entering the feeding port, the sharp tool box is linked with the discharge gate, is used for containing the medicine container and the residual medicine after smashing, and the sharp tool box is equipped with the reaction material that can react with residual medicine, and the review module is located between first feeding opening and the feeding port, and the review module is used for reviewing the information of medicine container to be destroyed, and the medicine container to be destroyed after review is put into the feeding port. The utility model provides technical scheme can be convenient to the information tracking of medicine itself, and the medicine container destruction is convenient, and the environmental pollution is reduced.

The application discloses a battery replacement cabinet safety control method based on an intelligent Internet of Things, relates to the technical field of thermal safety monitoring and control of a battery replacement cabinet, and utilizes a multivariate time sequence anomaly detection model combined with a long short-term memory autoencoder and an attention mechanism to extract deep features from voltage, current and environmental temperature data, effectively identify internal heat accumulation initial signals that are difficult to capture by external sensors, overcome the limitations of traditional fixed threshold monitoring, dynamically learn normal charging and discharging modes, sensitively capture subtle abnormal changes, thereby advance the early warning time, and reduce the risk of missed reports caused by surface temperature lag; a dynamic threshold mechanism is based on quantile numbers of a target false alarm rate and working condition parameters and is adaptively adjusted, so that the system can flexibly cope with complex factors such as different environmental temperatures and battery aging degrees, avoids the false alarm problem caused by a unified threshold, and improves the early warning accuracy.

The application discloses a kind of based on time-sharing user's rate time period exception checking method, equipment and medium, the method includes obtaining user rate time period agreement parameter and user profile information from marketing system, obtains electric meter rate time period parameter measurement data from metering automation system, daily frozen electric quantity data and load curve data, and data preprocessing is carried out to the data collected;Parameter checking matrix P and electric quantity checking matrix E are constructed;According to the preset timing trigger condition and event trigger parameter exception checking and electric quantity exception checking;According to the checking result, divide exception type, and carry out visual display;According to exception type, generate processing work order and push to operation and maintenance end, update parameter checking matrix P and electric quantity checking matrix E after processing result feedback, complete exception closed-loop management.The application effectively solves the problems of insufficient parameter measurement accuracy, single electric quantity checking dimension, missing dynamic checking mechanism and low efficiency of exception positioning in the prior art.

The application discloses a kind of coal mine electrical equipment intelligent safety locking systems, belong to electrical equipment safety monitoring technical field, it includes for creating, approving, issuing and archiving management to electrical equipment maintenance work ticket and generating work ticket data electronic work ticket management module;For real-time acquisition of the position information of underground maintenance personnel underground personnel accurate positioning system interface module;For connecting and controlling underground electrical equipment, according to control instruction to intelligent power supply unit is opened or closed intelligent power supply unit interface module and for according to work ticket data, position information carries out "people-ground-ticket" trinity authentication and generates control instruction according to authentication result AI intelligent association and decision engine.The coal mine electrical equipment intelligent safety locking system and method provided by the application can deeply integrate personnel position, operation permission, equipment status and remote authorization, fundamentally eliminate the possibility of maintenance misoperation.

This invention discloses a smart tunnel construction safety monitoring and early warning system and method, belonging to the field of tunnel engineering monitoring technology. The method includes: collecting construction quality data and environmental data during tunnel construction; preprocessing the data and extracting key features from the preprocessed data to generate a daily data analysis report; generating dynamic thresholds for construction quality data based on the Dynamic Adaptive Threshold Optimization Model (DATOM); adjusting early warning triggering conditions according to real-time construction stage labels; and sending alarm information to terminal devices when construction quality data and environmental data deviate from the thresholds to reach the early warning conditions. This invention can meet the needs of dynamic changes in monitoring parameter thresholds at different construction stages, and has relatively high accuracy in safety monitoring and early warning.

The invention belongs to hot equipment for heat supply in the building industry, and particularly relates to a controllable valve rod type valve for a heat supply system. The lock body is fixedly arranged in a pipe opening in the right side of the valve body, a lock cylinder is arranged in the lock body and located on the outer side of the valve rod, a lock body chip, a lock body contact and a clutch mechanism are arranged in the lock cylinder, the clutch mechanism is in linkage connection with two limiting columns, two pairs of limiting column grooves are formed in the positions, corresponding to the two limiting columns, of the valve rod, and a battery and a controller are further arranged in the unlocking body. Wherein the controller comprises a communication unit, a Bluetooth device, a storage unit, a control chip, an identification unit and a buzzer, and the controller communicates with the lock body chip. The chip is additionally arranged in the lock body, the clutch mechanism is controlled through a chip program of the lock body, so that opening and closing of the valve rod are controlled, control over fluid by the ball core can be systematically controlled, a heat supply valve cannot be easily and mechanically opened, the control efficiency of a heating system is improved, and loss of a heat source is reduced.

The invention relates to the technical field of stainless steel processing devices, in particular to a steel belt oiling device and an oiling method thereof. The technical scheme comprises: a frame; the conveying rollers are rotationally connected into the frame; the driving part is arranged between the frame and the conveying roller; the oil coating assembly is arranged in the frame; each group of oiling assembly comprises a mounting bin which is fixedly connected to the frame; the distribution layer is fixedly connected to the bottom of the frame; the adding pipe is fixedly connected into the mounting bin; and the control panel is connected to the cloth scattering layer in a sliding manner. By adopting an intermittent opening and closing structure of the baffle ring to the through opening, accurate quantitative supply of anti-rust oil is realized, and oil waste is remarkably reduced, so that the problems of excessive oil use, flowing accumulation, poor uniformity and the like caused by traditional continuous oil coating are solved; and the distribution layer is matched with the intermittent oil supply mode, so that the uniformity and consistency of oil film coating are ensured.

This invention relates to the field of vehicle-to-everything (V2X) technology and discloses a method for allocating D2D (Device-to-Device) resources in V2X based on dual-threshold cooperative reservation. The method includes: a base station periodically acquiring link status information of cellular users and D2D user pairs within the V2X coverage area, and calculating the signal-to-interference-plus-noise ratio (SINR) of the D2D link; dividing the SINR into three intervals using preset handover and reservation thresholds to determine the corresponding operating modes of the D2D user pairs; constructing a weighted bipartite graph based on the operating modes and service priority weights of the D2D user pairs, and performing user-resource block matching and allocation using a weighted Hungarian algorithm, marking the resource blocks matched by users in the cooperative reservation mode as reserved; periodically monitoring the status of reserved resource blocks, and releasing the corresponding resource blocks to the available resource pool when preset release conditions are met. This invention can improve the spectrum resource utilization rate of V2X D2D communication systems under limited spectrum resource conditions.

The application relates to the technical field of inventory strategy optimization, in particular to an intelligent inventory dynamic optimization method and system based on AI prediction, which comprises the following steps: collecting inventory decision data and preprocessing the inventory decision data; based on the preprocessed inventory decision data, a feature vector reflecting inventory fluctuation and demand trend is extracted through an inventory pressure conduction learning method; based on the feature vector, a long short-term memory network model is used to generate a future demand prediction value, an advance period demand distribution parameter is calculated according to the future demand prediction value, a Heckman two-stage model is used to correct the future demand prediction value, and a corrected advance period demand distribution parameter is generated based on the corrected future demand prediction value; and based on the corrected advance period demand distribution parameter, an out-of-stock event is constructed, and an out-of-stock probability is calculated. The application accurately extracts topological conduction features reflecting the inventory pressure conduction of the whole network by constructing a time sequence dynamic directed graph and performing multi-layer graph attention propagation.

The application discloses a power plant equipment two-dimensional code standardization generation and analysis management system based on KKS coding, comprising a server and a mobile terminal. The data preprocessing module of the server carries out semantic vectorization processing on the KKS coding and generates a dynamic hash index; the two-dimensional code coding module adopts a non-uniform redundancy distribution mode, distributes the core semantic section to the two-dimensional code center high-redundancy protection area, and distributes a lower redundancy factor or a predictive error correction bit to the edge area; the data feedback module returns adaptive display content based on an identity tag. The mobile terminal analysis module preferentially decodes the center area to extract the system attribution vector in an offline state, combines a local process logic library and auxiliary positioning information to restore the equipment information through probability matching recursion; meanwhile, the dynamic hash index and the identity tag can be sent to the server to obtain online display content. The application significantly improves the recognition rate under oil stain shielding, realizes offline analysis, reduces the label reprint cost, and supports role differentiation information display.

The present application relates to the technical field of medical informatics, and is a child rehabilitation training management method and system based on an AI chip, comprising: collecting multi-modal original data by using the AI chip, including three-dimensional coordinates of skeletal joint points and gaze point trajectory features; executing a quantitative evaluation mapping program, mapping clinical scale evaluation indexes into feature loss functions and performing localized feature extraction to generate desensitization feature vectors; performing homomorphic encryption on the desensitization feature vectors and calculating local weight gradient information to be sent to the cloud, while keeping original data stored locally on the edge; receiving multi-terminal gradient information on the cloud and running a federal learning program to perform weighted aggregation, generating and issuing a global education plan recommendation model to update local parameters; calling a SHAP explainability framework to perform attribution analysis to determine contribution weight values and fill in a clinical note template to generate a structured rehabilitation evaluation report. The present application realizes quantitative evaluation and automatic generation of clinical reports under medical data privacy protection.

The application discloses a kind of intelligent community property management methods based on image recognition technology, it is related to image recognition technology field, including, calibration each camera picture in property space anchor point, and the object handover line between adjacent camera is associated, configuration space connection relationship, form anchor point connection set;Using anchor point connection set to identify the property object in real-time video stream, determine the contact relationship and action state of property object and property space anchor point, and arrange anchor point contact sequence according to time sequence, form event fragment set;Verify the reset state of the corresponding terminal anchor point of disposal page, and continue video identification and event continuation when terminal anchor point is not reset, form property disposal record.The application realizes the closed-loop management of event disposal by the continuous verification of terminal anchor point reset state and the dynamic continuation under the condition of not resetting.

The utility model discloses a kind of coal winning machine maintenance-free sprocket sets, belong to coal winning machine sprocket technical field, comprising: first sprocket and second sprocket;Mounting groove, open in first sprocket side, second sprocket one end is in mounting groove, first sprocket and second sprocket are all equipped with mounting hole, two The mounting hole is equipped with the same mounting rod;Positioning groove, open in two mounting holes, the mounting rod outside is equipped with the mounting ring compatible with positioning groove;The utility model, through the oil inlet channel and oil discharge channel being arranged in mounting rod and mounting ring, the closed-loop management of sprocket set lubricating system is realized, old grease discharge and new grease filling can be completed without repeatedly disassembling sealing assembly, not only significantly reduce the coal dust invasion risk, avoid the performance attenuation caused by sealing element frequent disassembly, also save the time and manpower to grease replacement, so that the convenience of coal winning machine maintenance-free sprocket set use is better.

The invention discloses a BIM (Building Information Modeling)-based super-dangerous large project prediction and identification system and method, and relates to the technical field of project safety management. The system comprises a prediction and identification model management module, an automatic prediction and identification module, a result output module, a construction scheme auxiliary compiling module, a management auxiliary module and an intelligent early warning module. According to the method, a deep foundation pit engineering prediction and identification model, a concrete formwork supporting engineering prediction and identification model, a hoisting and hoisting machinery mounting and dismounting engineering prediction and identification model, a scaffold engineering prediction and identification model and a building curtain wall mounting engineering identification model are constructed; a steel structure installation project prediction identification model and a manual hole digging pile project prediction identification model are combined with a BIM model of an uploading platform to carry out automatic prediction identification of a super-dangerous large project, a construction scheme is compiled in an auxiliary mode, identification omission is avoided, meanwhile, whole-process flow auxiliary monitoring is formed, and closed-loop management is achieved.

The invention discloses a dynamic safety management and control system and method based on an intelligent lock, and relates to the field of intelligent management and control, firstly, a background management platform generates an authorization data packet according to an operation task and issues the authorization data packet to a key management machine, and after an operator passes identity authentication, an intelligent key obtains authorization and interacts with a target lock; and after the verification is passed, the intelligent key drives the lock to open, reads the physical state of the lock after unlocking, sends state information to the key management machine through the real-time communication module, and finally uploads the state information to a background platform for analysis and database updating. According to the scheme, closed-loop management of authority control, operation verification and state feedback is achieved, safety and management efficiency are improved, real-time synchronization and traceability of the lock state are ensured, and remote monitoring and risk early warning are effectively supported.

This invention relates to the field of intelligent diabetes management technology, specifically to an intelligent management method and system for the entire diabetes lifecycle. The invention constructs four independent specialty models: a metabolic progression assessment model, a cardiovascular risk assessment model, a kidney damage assessment model, and a retinopathy assessment model. Each model outputs its corresponding specialty's risk probability, confidence level, and evidence feature vector. A global arbitration decision model then generates dynamic weights for each specialty model based on the output results, user's global background features, knowledge graph embedding, and historical state memory. This achieves weighted fusion of the model output layers, constructs a strategy optimization model, coordinates knowledge graph constraints, and generates individualized intervention plans and management reports. This invention solves the technical problem that a single model cannot adequately consider the independent pathophysiological mechanisms and clinical assessment logic of multiple complications, improving the accuracy and interpretability of diabetes lifecycle prediction, multi-complication risk warning, and individualized management.

This utility model belongs to the field of construction site dust suppression technology, specifically a construction site dust suppression device, including a base plate. A lifting plate is provided in the middle of the top side of the base plate. Mounting plates are fixedly connected to the front and rear sides of the top of the lifting plate. An atomizing cylinder is rotatably installed between the two sets of mounting plates. This utility model actively collects dust particles that do not settle during the spraying process of the atomizing cylinder through the dust collection port, and combines it with the spray treatment in the spray tank to effectively prevent secondary dust. At the same time, the return component filters the wastewater and circulates it to the water tank to realize closed-loop management of water resources. In addition, the modular design of the filter plate, connecting pipe and sealing cover structure supports quick disassembly and replacement, which is convenient for cleaning blockages or replacing filter elements.

The embodiment of the application discloses a mine gushing water source identification and early warning system, relates to the technical field of mine safety production, and is convenient for realizing closed-loop management from risk discovery to risk elimination. The system comprises: a water source identification module, which is used for identifying the water source type of the water sample to be identified based on water quality index data; an early warning generation module, which is used for matching preset early warning rules according to the identification result and generating hierarchical early warning information; an information pushing module, which is used for pushing the hierarchical early warning information to the terminal equipment of the corresponding person in charge according to the early warning level and a preset pushing strategy; a disposal closed-loop module, which is used for storing the disposal record in association with the corresponding identification result and early warning information to form a complete closed loop from identification to disposal; and a platform interfacing module, which is used for pushing at least one kind of data in the stored identification result, early warning information and disposal record to an external platform to realize data sharing and business cooperation. The application is suitable for the scene of mine gushing water source identification and early warning.

The invention provides a power grid multi-node operation collaborative management and control method and system based on intelligent scheduling, and the method comprises the steps: building an initial operation diagram through obtaining the task information of various types of operations of a scheduling center, a photovoltaic power station operation end and an energy storage system management end; performing graph structure coding on the job node features, the external operation state and the electrical risk information based on a graph neural network, generating a graph embedding representation reflecting the job dependency relationship and the risk coupling characteristic, and triggering the dynamic structure adjustment of the job graph by calculating the node risk exposure value and the edge risk coupling degree in real time, so as to obtain the dynamic structure of the job graph. And obtaining a target job diagram for collaborative scheduling. The method is used for multi-agent cooperative execution, continuously triggers operation graph adjustment and strategy updating according to a real-time operation state, and forms a dynamic closed-loop management and control mechanism of power grid multi-node operation. According to the method, multi-subject and multi-task intelligent cooperation of power grid power-on and power-off operation, photovoltaic energy storage grid-connected detection and the like can be realized, and the operation safety and the grid-connected stability are improved.

The invention discloses a shared vehicle reservation method and device, a vehicle and a computer readable storage medium. The method comprises the steps that vehicle reservation information of a target user is acquired; matching the vehicles meeting a preset condition, and generating a matching result; wherein the preset conditions include elimination of vehicles with faults, insufficient residual endurance, reservation conflicts and exceeding the vehicle use range; pushing a matching result and cost estimation, and obtaining a user confirmation instruction to generate a vehicle reservation order; wherein the reservation order comprises use permission information of the target vehicle corresponding to the matching result; and obtaining the use state of the target user on the target vehicle, and generating a fee bill after the vehicle use is finished. By applying the technical scheme of the invention, the technical problem that the user cannot find the vehicle to use after arriving at the vehicle taking point due to the fact that the problems of vehicle fault, insufficient endurance, reservation conflict, geographical range limitation and the like are not comprehensively considered in the vehicle matching process of the existing shared vehicle platform can be solved.

The invention discloses a product quality inspection management system and method, and belongs to the field of product quality inspection and control. The system comprises the following modules: a network topology construction module which dynamically constructs a network topology structure based on multi-source inspection data and realizes time-space correlation analysis of a quality state; the anomaly detection module is used for identifying an abnormal node and positioning a risk source through an anomaly detection algorithm; the influence degree calculation module responds to the anomaly identification output by the anomaly detection module and quantifies the diffusion range and intensity of the anomaly association relationship in the whole quality analysis system based on a propagation model; the evaluation index module is used for constructing a multi-dimensional quality evaluation index system and calculating the relative weight of each index by adopting an analytic hierarchy process; and the early warning monitoring module monitors the change of the network topology structure and an influence degree calculation result in real time, identifies abnormal association of different severity degrees in combination with a graded early warning threshold value, and starts a differentiated dynamic monitoring and handling mechanism.

The embodiment of the invention provides an abnormal data processing method and device, equipment, a storage medium and a program product, and relates to the field of financial science and technology. The method comprises the steps of obtaining a to-be-processed data table; extracting a blood relationship corresponding to the to-be-processed data table according to a to-be-executed script corresponding to the to-be-processed data table; according to the blood relationship, constructing a blood relationship topology network through a graph neural network in combination with a preset verification rule; and when it is detected that the abnormal data exists in the to-be-processed data table, determining a source node corresponding to the abnormal data by using the blood relationship topology network, and repairing the abnormal data by using the preset knowledge base. According to the method provided by the invention, through combination of data blood relationship modeling and graph neural network dynamic analysis, the efficiency and accuracy of financial data governance are remarkably improved; the range of occurrence of the abnormal data can be quickly delineated, the time of tracing the abnormal data is greatly shortened, and the efficiency of tracing the abnormal data is greatly improved.

The utility model discloses a multifunctional grain condition processing machine relates to grain storage technical field, including frame, the bottom of frame is equipped with walking mechanism, and the top is equipped with the grain turnover mechanism, the grain turnover mechanism includes the scraper conveyor hinged in the front end of frame, still includes setting up the back slide screen in the rear end of frame, and the scraper conveyor and back slide screen all are obliquely arranged, and the upper end of back slide screen is hinged below the output end of scraper conveyor, electric telescopic link I is hinged between the scraper conveyor and frame, and electric telescopic link II is hinged between back slide screen and frame, and the input end fixed mounting of scraper conveyor has the feeding hopper, and the rotatory axle is rotatoryly installed in the feeding hopper, and the rotatory axle is transmission connection with scraper conveyor. This multifunctional grain condition processing machine, integration removes, grain, screening, dosing function, single operation can complete multiple tasks simultaneously, and the manual cost is reduced greatly, realizes "turnover - purification - protection " closed - loop management, fundamentally solves the problem of the grain condition in the warehouse out of control.